Dr. Jianhong Wu
Biography: Jianhong Wu is a Fellow of the Royal Society of Canada, a Fellow of the Canadian Academy of Health Sciences, and a Fellow of the Fields Institute. He is the inaugural Director of the York Emergency Mitigation, Engagement, Response, and Governance Institute (Y-EMERGE), the founding Director of the Laboratory for Industrial and Applied Mathematics (LIAM), and the founding Director of the Fields Laboratory of Mathematics for Public Health (MfPH). He received his PhD from Hunan University in 1987, and received Doctor Honoris Causa, from University of Szeged (nominated by the Byloai Institute). He was the Tier I Canada Research Chair (2001-2022), followed by the York Research Chair (2022-) in Industrial and and Applied Mathematics.
Research Interests: Industrial and Applied Mathematics, and whatever makes the interdisciplinary research and academic-industrial-public collaboration successful.
Dr. Woldegebriel Assefa Woldegerima
Biography: Dr. Woldegerima is a newer faculty member as an Assistant Professor at the Department of Mathematics and Statistics at York University. He was a Postdoctoral Research Fellow at the Mathematical Models and Methods in Biosciences and Bioengineering Lab at the University of Pretoria, South Africa. PhD Thesis on “Mathematical Modeling and Analysis of the Immunopathogenesis of the Within Human-host and Within Vector-stage Dynamics of Parasites”. He is certified in Supervised and Unsupervised Machine Learning from DeepLearning.AI at Stanford University.
He has earned two master’s degrees: one from the African Institute for Mathematical Sciences (AIMS) with a master's thesis in partial differential equations, and a second master of science degree from Addis Ababa University in Ethiopia in Functional Analysis.
My researchgate's website: https://www.researchgate.net/profile/Woldegebriel-Assefa-Woldegerima-2
My York U personal website: https://www.yorku.ca/professor/waw/research-interests/
Research interests: In-host modeling, infectious disease modelling and prediction; Modelling the impact of climate change on infectious disease dynamics; Machine learning approaches for modeling and disease prediction; Muti-time scale modeling; Neural differential equations.
